Neuromuscular Function and Blood Flow Occlusion with Dynamic Arm Flexor Contractions
Bibliographic record
Abstract
INTRODUCTION: Blood flow-restricted or occlusion exercise enhances muscle hypertrophy and strength during resistance training. The acute effects on voluntary and electrically evoked muscle contractile characteristics with impaired blood flow at low- and high-contraction forces have not been explored. METHODS: On separate days, nine males completed two different protocols of concentric elbow flexor contractions. A repetitive low-force (~25% of isometric maximum voluntary contraction [MVC]) with blood flow occlusion (BFO) (300 mm Hg) protocol was compared with a high-force (~80% MVC) free blood flow protocol (HF), until range of motion (0°-90°) was impaired. Torque, velocity, and power were compared with baseline and between protocols. Maximum voluntary contraction and voluntary activation were assessed during and after each protocol. Muscle twitch, low (20 Hz) and high (50 Hz) tetanus, and compound muscle action potential (Mmax) area were measured at 0, 2, 5, 10, and 20 min of recovery. RESULTS: Repetitions to failure (FP) were lower for HF (~16) versus BFO (~21), and MVC at FP was reduced more during BFO (~77%) compared with HF (~23%), with no difference in voluntary activation (~10% loss) between protocols. At FP, velocities for BFO and HF were similarly reduced by approximately 63% and 56%, respectively; however, peak power decreased more during BFO (~90%) compared with HF (~67%). Total work for BFO was approximately 40% lower than for HF. Peak power for HF was recovered by 2 min, whereas BFO required 20 min. Low-frequency fatigue (20 Hz/50 Hz) was greater after BFO (~70% decrease vs ~29% decrease after HF), whereas Mmax area was unaffected. CONCLUSION: Concentric elbow flexions at low-force with BFO cause greater impairments in strength and power than HF and, therefore, may be a replacement for high-force exercise used in chronic training.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".